Atomic-Scale Intercalation of Graphene Layers into MoSe2 Nanoflower Sheets as a Highly Efficient Catalyst for Hydrogen Evolution Reaction

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)2460-2468
Number of pages8
Journal / PublicationACS Applied Materials and Interfaces
Issue number2
Online published26 Dec 2019
Publication statusPublished - 15 Jan 2020


MoSe2 is an efficient catalyst for the hydrogen evolution reaction (HER) and can potentially replace conventional catalysts composed of noble metals such as Pt. The HER activity of MoSe2 originates mainly from the edge sites of Se atoms, but the low concentration of Se exposed to the electrolyte hampers the performance. Hence, activating a larger portion of the basal plane of Se atoms is an effective way to improve the HER properties. Herein, a 3D hierarchic nanoflower structure comprising MoSe2 with atomic-scale interlayered graphene layers in the nanosheets is designed and prepared to improve the electron conductivity and decrease the proportions of inactive basal planes. Raman scattering, transmission electron microscopy, and energy-dispersive X-ray spectroscopy verify effective insertion of graphene layers in MoSe2, and the HER characteristics are improved as exemplified by a small overpotential of 175 mV at 10 mA cm-2, small Tafel slope of 58 mV dec-1, and excellent durability with only small deterioration of 10 mV after 10,000 cycles. First-principles density functional theory and finite element method calculations corroborate the experimental results, revealing better conductivity and hydrogen adsorption/desorption ability rendered by the graphene layers. Our results reveal a new and effective strategy to optimize the structure and composition and reduce the hydrogen adsorption energy barrier in the pursuit of high-efficiency non-noble metal catalysts.

Research Area(s)

  • hydrogen evolution reaction, intercalated graphene, MoSe2, sandwiched structure, theoretical derivation

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